Method and system for electronic advertising

ABSTRACT

A method of delivering advertising in an online environment includes determining an intent of a user interacting with an e-commerce website, and determining a hurdle rate that is based at least on the user intent and which identifies a threshold amount to be bid by an advertiser in order to display an advertisement to the user. The method further includes selecting, from a plurality of advertisements, an optimal advertisement having an advertiser bid that exceeds the hurdle rate, and displaying the optimal advertisement to the user in an interface of a client computer system.

RELATED APPLICATIONS

This application claims priority under 35 U.S.C. §119(e) to U.S.Provisional Application Ser. No. 61/184,032, entitled “METHOD ANDAPPARATUS FOR ELECTRONIC ADVERTISING,” filed on Jun. 4, 2009, which isherein incorporated by reference in its entirety.

BACKGROUND OF INVENTION

1. Field of Invention

The present disclosure relates generally to Internet technologies, andmore specifically, to online advertising.

2. Discussion of Related Art

Online advertising is one form of marketing where advertisements (ads)are distributed to users generally through a communication network suchas the Internet. Advertised products include goods and services. In onetypical system, a user utilizes a web browser application program on apersonal computer (PC) to access a webpage by supplying a UniformResource Locator (URL). The webpage is provided by an online (or web)publisher. Upon accessing the webpage, an advertisement is displayed tothe user within a computer interface.

Systems have been developed that display certain advertisements to auser based on information provided by the user, or based on the contentof the page which the user is viewing. For example, when the user enterswords, phrases, or other terms into an online search engine,advertisements related to the search terms or search results aredisplayed by the publisher of the web page, which typically is thesearch engine service. In some instances, the advertisements are chosenbased on other information, such as user identification or browsinghistory. These types and other types of contextual advertising attemptto target the intent of the user (e.g., where the user is shopping for aparticular product). Such targeted advertising is known to increase thechance of attracting interest in the advertised product, which in turnincreases the value of the advertisement. Advertisers bid for placementof their ads, with the bids reflecting a monetized value of the user'sintent, and pay the bid amount to the publisher if and when the ad isdisplayed.

SUMMARY OF INVENTION

A method and system for electronic advertising is described herein. Itis appreciated that on a typical e-commerce website operated by apublisher, where certain goods and/or services are sold, a vast majorityof visitors to the first website do not complete a sales transaction,which is referred to in the art as a “conversion”. In fact, a typicale-commerce website has a conversion rate of 3%-5%. Thus, it isappreciated that visitors primarily use some e-commerce websites tobrowse and research products. For instance, visitors may researchproduct features, price, availability, reviews, and comparisoninformation on such websites without making any purchases. Often, afteracquiring the desired information about a particular product from thewebsite, the user will locate and purchase that product from anothersource, for example on another website operated by a different publisheror complete the transaction using another channel (e.g., telephoneorder, brick-and-mortar store).

In one example, the user may find that the e-commerce website provides aconvenient place to research and/or comparison shop, but once apurchasing decision is made the user exercises his or her preference forpurchasing certain products directly from a manufacturer or a trustedretailer, rather than from the publisher. Specifically, a user uses anonline travel service, such as Expedia® online travel website byExpedia, Inc., to shop for airline tickets, but after locating thedesired itinerary and fare, the user ultimately purchases the ticketsdirectly from the airline and not from the Expedia website. In anotherexample, the visitor does not find what he or she is looking for on thefirst website, and leaves the website without completing a transaction.

When no transaction occurs on the website, the publisher receives norevenue from the visitor. According to one aspect, it is appreciatedthat most e-commerce websites monetize their visitors exclusively, oralmost exclusively, through transaction (or sales) revenue. In someinstances, a publisher receives a stream of advertising (or media)revenue for serving ads on their website for various goods and servicessold by others. The media revenue, if any, is generally used tosupplement the transaction revenue. However, when the ads are for acompeting (or the same) product sold by another, the publisher may bereluctant to display the ad to its visitors out of concern that suchaction will cannibalize sales, and thus the publisher may prefer toforgo the potential media revenue.

According to one aspect of the present disclosure, a contribution pervisitor (CPV) to an e-commerce website may be determined, and this CPVmay be used to determine when and if ads are displayed on an e-commercewebsite. According to one embodiment, CPV is a measure of the profit ornet revenue received by the publisher of the website for each visitor.Such revenue may be created by sales, advertising, or both. In oneexample, the CPV may be based, at least in part, on the average netrevenue generated by each visitor over some finite period of time, wherenet revenue includes transaction and/or media revenue. It is appreciatedthat the CPV can be improved or maximized by optimizing transactionrevenue and media revenue, for example, by evaluating the effect ofdisplaying ads on a visitor-by-visitor basis and displaying ads wherethe potential benefit of receiving ad revenue exceeds the potential lossin transaction revenue resulting from displaying the ad. It should beunderstood that the measures of determining the CPV and/or performingthe benefit/cost analysis described above are merely exemplary and thatother measures may be used.

It is also appreciated that the visitor's intent to purchase aparticular product may be determined based on the visitor's interactionwith the website, and that such intent may be monetized by, for example,allowing advertisers to bid for the opportunity to place ads that aretargeted to the intent of the visitor on the website. The ads may, forexample, enable the visitor to discover additional retailers, products,product substitutes, complementary products, and prices. Where the valueof the media revenue (e.g., the bid amount) exceeds a threshold amount,displaying the targeted ad increases the CPV relative to the CPV where anon-targeted ad, or no ad, is displayed.

According to an embodiment of the disclosure, a method for deliveringelectronic advertising includes identifying an intent of a visitorinteracting with an e-commerce website, determining a hurdle rate thatidentifies a threshold amount to be paid by an advertiser in order todeliver an advertisement to the user at the e-commerce website based onthe intent, selecting an optimal advertisement from a plurality ofadvertisements having an advertiser bid greater than or equal to thehurdle rate, and delivering the optimal advertisement to the visitor inan interface of a client computer system. Visitor intent may include aspecific intent of the visitor, for example, an intent that is resolvedto a relatively high degree of granularity, such as an intent to travelto a specific city, stay at a specific hotel, travel on a certain date,or eat at a restaurant in a specific neighborhood. Specific intent mayalso include specific dates or ranges of dates associated with, forexample, a trip. The hurdle rate may reflect the value of serving an adto a particular visitor, given the known intent of the visitor. Forexample, ads targeting a specific intent may be more valuable than adsdirected toward a general intent or non-targeted ads.

In addition to determining a hurdle rate based on intent, the selectedadvertisement may be adapted to target visitor intent (e.g., providingan offer that may satisfy the visitor's intent, such as an offer for aspecial rate at a hotel specified by the visitor). Further, an intentstage (or process context) of the visitor may be determined based on thevisitor's interaction with the website, for example, whether the visitoris shopping (or browsing) for a product, selecting a product, orpurchasing a product. The intent stage may be used to optimize theselection of ads that are displayed to the visitor.

According to another embodiment, the method of delivering electronicadvertising may include receiving an advertisement request from apublisher of an e-commerce website. The advertisement request mayinclude one or more keywords, wherein an intent of a user is based atleast in part on the keywords.

The method may further include translating the advertisement requestinto one or more intent targets. Translating the advertisement requestmay include selecting each of the one or more intent targets from aplurality of normalized intent targets based on information included inthe advertisement request, wherein the plurality of normalized intenttargets is stored in an intent target taxonomy database. The hurdle ratemay be adjusted in relation to the one or more intent targets.Determining the hurdle rate may also include adjusting the hurdle ratebased on a historical average conversion rate of each of the one or moreintent targets, and adjusting the hurdle rate based on an averagecontribution margin of a completed transaction for the one or moreintent targets.

The method may further include translating the advertisement requestinto one or more process contexts. Translating the advertisement requestmay include selecting each of the one or more process contexts from aplurality of normalized process contexts based on information includedin the advertisement request, wherein the plurality of normalizedprocess contexts is stored in a process context taxonomy database.Determining the hurdle rate may also include adjusting the hurdle ratebased on the one or more process contexts.

The method may further include selecting, from a plurality ofadvertisements, one or more candidate advertisements, wherein an optimaladvertisement is selected from the one or more candidate advertisements.

It is further appreciated that it is desirable for advertisers to tailoradvertising towards the specific intent of a consumer, which may befacilitated by various computer technologies. Accordingly, variousembodiments of systems and methods disclosed herein may operate andoccur in real-time, where visitor intent and intent stageidentification, hurdle rate calculation, advertisement creation,advertisement selection and advertisement display are responsive inreal-time to visitor interaction with the e-commerce website. Otheraspects of the invention may also be performed in real-time. Forexample, advertisers may bid in real-time based on the intent, intentstage, and/or other information received from a publisher of thewebsite, such as visitor status, visitor past purchases, and trafficsource (e.g., describing how the visitor arrived at the website, such asfrom an affiliate website or a web browser bookmark). Such real-timebidding enables advertisers to easily direct targeted marketingcampaigns toward visitors of interest to the advertiser while avoidingcosts associated with less controlled advertising distribution methods.

According to another embodiment, a method for delivering electronicadvertising includes identifying one or more characteristics of avisitor to an e-commerce website, determining a hurdle rate fordisplaying an advertisement to the visitor based at least on thecharacteristics, determining whether to display an advertisement basedon the characteristics, and if so, selecting an advertisement based onan intent of the visitor, wherein the selected advertisement is offeredby an advertiser for at least the hurdle rate, and displaying theselected advertisement to the visitor in an interface of a clientcomputer system. For example, the characteristic of the visitor may be ahigh value visitor or a low value visitor. The value of the visitor maybe, for example, determined based on how the visitor was acquired (e.g.,through a paid search, a natural search, or an e-mail), or based onintra- and inter-session behavior of the visitor at the website. Adsselected for display may be targeted to the visitor (or not displayed atall) based on the value of the visitor, or based on othercharacteristics, such as whether the visitor is a registered user, areturn visitor, or a loyalty program member.

According to another embodiment, a method for delivering electronicadvertising includes identifying an intent of a visitor to an e-commercewebsite and identifying an intent stage of the visitor, selecting anadvertisement from a plurality of advertisements based on the intent andthe intent stage, and displaying the selected advertisements to thevisitor. For example, if the intent of the visitor is to purchase a flatscreen TV and the intent stage is “purchased,” an ad for Blu-Ray discplayers is relevant to the intent because it promotes complementaryproduct discovery, and the ad is also relevant to the intent stagebecause the visitor, having purchased the TV, is likely to purchase thedisc player to complement the TV.

According to another embodiment, a method for delivering electronicadvertising includes determining an intent of a user interacting with ane-commerce website, providing one or more controls in a user interfaceof a client computer system, each of the controls being associated withan advertiser and adapted to enable the user to select one or more ofthe advertisers, and providing an element responsive to the input of theuser that is adapted to display an advertisement from one or more of theadvertisers based on the intent.

According to yet another embodiment, a method of delivering advertisingin an online environment includes determining an intent of a userinteracting with an e-commerce website, determining a hurdle rate, basedat least on the intent of the user, that identifies a threshold amountto be bid by an advertiser in order to display an advertisement to theuser interacting with the e-commerce website, selecting, from aplurality of advertisements, one or more optimal advertisements having acombined advertiser bid that exceeds the determined hurdle rate,providing one or more controls in a user interface of a client computersystem, each of the one or more controls being associated with arespective advertisement of the one or more optimal advertisements andadapted to enable the user to select one or more of the one or morecontrols, and providing an element, responsive to an input of the user,that is adapted to display, to the user, the one or more respectiveadvertisements selected by the user.

According to another embodiment, a method of delivering advertising inan online environment includes determining a context of a user operatinga client computer to interact with an e-commerce website, the determinedcontext representing an intent of the user to locate a product forpurchase, defining a relation between one or more of a plurality ofadvertisements and the product based on at least one of a plurality ofrelevance types, and displaying, to the user, at least one of theadvertisements having the relation to the product. The method may alsoinclude categorizing one or more of the plurality of advertisementsaccording to at least one of the plurality of relevance types.

According to yet another embodiment, a method of delivering advertisingin an online environment includes receiving an advertising campaignincluding one or more advertisements for one or more advertised productsand associating the one or more advertisements with one or morekeywords, wherein each of the one or more keywords represents theadvertised products. The method may further include determining anintent of a user interacting with a website to purchase a product basedon one or more user supplied keywords. The method may further includedetermining a hurdle rate, based on the intent of the user, thatidentifies a threshold amount to be bid by an advertiser in order todisplay an advertisement to the user, and displaying, to the user in aninterface of a client computer, one or more of the advertisements thatare associated with the user supplied keywords and that have bids thatexceeds the hurdle rate. The method may further include receiving, froma publisher of the website, an advertisement request includinginformation related to the intent of the user.

BRIEF DESCRIPTION OF DRAWINGS

The accompanying drawings are not intended to be drawn to scale. In thedrawings, each identical or nearly identical component that isillustrated in various figures is represented by a like numeral. Forpurposes of clarity, not every component may be labeled in everydrawing. In the drawings:

FIG. 1 is a schematic diagram of an exemplary system in accordance withone embodiment of the present disclosure.

FIG. 2 is an exemplary system diagram in accordance with one embodimentof the present disclosure.

FIG. 3 is an exemplary system architecture diagram in accordance withone embodiment of the present disclosure.

FIG. 4 illustrates an exemplary process for delivering advertising inaccordance with one embodiment of the present disclosure.

FIG. 5 illustrates an exemplary process for calculating a hurdle rate inaccordance with one embodiment of the present disclosure.

FIGS. 6A-B illustrates exemplary processes for generating a list ofcandidate advertisements in accordance with one embodiment of thepresent disclosure.

FIG. 7 illustrates an exemplary process for optimizing ad selection inaccordance with one embodiment of the present disclosure.

FIG. 8 illustrates an exemplary system for delivering advertising inaccordance with one embodiment of the present disclosure.

FIG. 9A illustrates an exemplary interface for a comparison shoppingwidget in accordance with one embodiment of the present disclosure.

FIG. 9B illustrates an exemplary method of one implementation of aconsumer shopping widget in accordance with one embodiment of thepresent disclosure.

FIG. 10 illustrates an exemplary media platform in accordance with oneembodiment of the present disclosure.

FIG. 11 is an exemplary system diagram in accordance with one embodimentof the present disclosure.

DETAILED DESCRIPTION

Embodiments of this invention are not limited in their application tothe details of construction and the arrangement of components set forthin the following description or illustrated in the drawings. Embodimentsof the invention are capable of other embodiments and of being practicedor of being carried out in various ways. Also, the phraseology andterminology used herein is for the purpose of description and should notbe regarded as limiting. The use of “including,” “comprising,” “having,”“containing,” “involving,” and variations thereof herein is meant toencompass the items listed thereafter and equivalents thereof as well asadditional items.

System Overview

According to one aspect of the present invention, a system and method isprovided to permit one or more advertisers to display one or moreadvertisements on, for example, an e-commerce website that is controlledby a publisher other than any of the advertisers. As discussed above, itmay be desirable for publishers and/or advertisers to display theadvertisement based on the intent of a user (also referred to as avisitor) interacting with the e-commerce website. For example, where theintent of the user is to purchase an airline ticket, an advertisementthat targets this intent (such as an advertisement for a particularairline) may be displayed to the user. Accordingly, in one embodiment,it is possible for advertisers to quickly and easily identify, forexample, which product, products, or class of products a user issearching for or intending to purchase, and to display advertisementstargeting the user on the basis of that knowledge. It should beunderstood that in some embodiments a publisher may also be anadvertiser, for example, a publisher that advertises on an e-commercewebsite operated by the publisher.

It may further be desirable for the publisher to optimize (or maximize)a contribution per visitor (CPV) by, for example, providing an auctionwhere advertisers enter bids for advertising space on the e-commercewebsite. In one example, a hurdle rate is determined based at least onthe calculated value of expected revenue derived from the user where noad is displayed on the e-commerce website. Where one or more advertiserbids match or exceed the minimum bid, advertisements associated with thebids may be displayed to the user visiting the e-commerce website. Inanother example, the hurdle rate may be determined based on acharacteristic of the user, such as whether the visitor is a high valuevisitor or a low value visitor. To these ends, a system and method maybe provided for displaying advertisements based on user intent in anauction-based environment.

Another aspect of the present invention relates to a process formonetizing the purchase intent of users across multiple e-commercesites. According to various aspects of the present invention, adistributed server-based system may serve advertisements to a number ofe-commerce websites based on user intent as determined by or from one ormore client systems. In one example, the client system may be abrowser-based system that permits the user to interact with e-commercesites. However, it should be appreciated that any type or combination ofclients may be used (e.g., thick or thin clients; different types ofclient systems, such as cell phones, PDAs, web servers, etc.; anddifferent types of programs, such as OSs, application programs, etc.).These other types of clients, programs and/or systems may provide suchintent information in real-time.

According to one embodiment, one or more components may be provided thatdetermine the intent of a user viewing an e-commerce website andidentify one or more advertisements that target the intent. Forinstance, a component that resides on an e-commerce site may track useractivity and/or context and select advertisements that match thatactivity and/or context.

According to another embodiment, there may be a threshold advertisingrate that is used to determine whether or not particular ads aredisplayed, which is similar to a reserve price in an auction. Forinstance, a “hurdle rate” may be calculated that defines a costthreshold that an advertiser would need to pay in order to display theirads on another e-commerce website. In one example, the hurdle rate mayrelate to the amount of expected profit that could be realized bydisplaying a particular ad on an e-commerce website tempered by therealization (or conversion) rate typically experienced by the website.In another example, the hurdle rate may also relate to the expectedtransaction net revenue in, for example, a particular process context.Further, the hurdle rate may also relate to the return-to-purchase rate,which is a measure of how often a visitor returns to the e-commercewebsite to make a purchase after having left to visit another websiteprior to the purchase (e.g., a visitor who may be “shopping around”).Depending on the product being offered on the e-commerce site, thehurdle rate, and the conversion rate, a decision engine may determinewhether or not an ad is displayed to the user at a particular contextwithin the e-commerce site.

The one or more components that perform these functions may be executedon one or more general purpose computer systems. For instance, one ormore of these components may execute as processes on a server, a client,or both in association with an e-commerce site.

FIG. 1 illustrates a schematic overview of an exemplary system accordingto an embodiment of the disclosure. Shown is an interface of a clientcomputer 101, such as a web browser, a publisher 102 of an e-commercewebsite, a media platform 104, and an advertiser 106. Media platform 104may be a computer server or a distributed computer system on whichvarious embodiments of the present disclosure may be implemented,including, but not limited to, determining an intent of a visitor to ane-commerce website, determining a hurdle rate, selecting an optimaladvertisement, and displaying the optimal advertisement to the visitor.There may be more than one interface 101, publisher 102, and advertiser106. Publisher 102 provides one or more web pages (not shown) to a userthrough interface 101. The user interacts with the e-commerce websitethrough the user interface to identify, locate, and/or purchase aproduct, for example, airline tickets or other item, by providing searchterms 110. Other information may also, or alternatively, collected fromthe user by publisher 102. This information may be used to determine anintent of the user, such as an intent to purchase airline tickets on aspecific day, or to a specific city, or other similar travel-relateddetails. It should be understood that the present disclosure is notlimited to travel products, but may include any products sold oradvertised through electronic commerce.

After the user enters search terms 110 (or other information), publisher102 sends an advertisement request 112 to media platform 104. Mediaplatform 104 uses the ad request to, among other activities, determine ahurdle rate 114 for serving an advertisement to the publisher. In oneembodiment, the hurdle rate is a minimum bid that must be received froman advertiser in order to serve the ad. It should be understood that thehurdle rate may include the minimum bid as well as other factors, suchas a minimum net transaction revenue or minimum media revenue, amongothers. In one example, the minimum bid may be based on a reserve priceof an auction, where the auction is for the opportunity to display oneor more selected advertisements to a website visitor. The minimum bidmay reflect the monetized value of an identified intent of the visitorto, for example, purchase a product. Further, the hurdle rate mayrepresent a combination of bids from multiple advertisers, such as in amulti-ad unit, which is described below. For example, a multi-ad unitmay not be served to a publisher unless the combination of all bids foreach ad in the multi-ad unit exceeds the hurdle rate.

The minimum bid may be determined in real-time and may be determinedfrom information included in the ad request. Advertiser 106 may alsoreceive information regarding the intent from publisher 102 throughmedia platform 104, and may place an advertising bid 116 based on theintent (or other information included in the ad request) if, forexample, the advertiser desires to advertise to the user.

Next, media platform 104 selects an optimal ad 118 based at least on theintent and the bid (or bids, if multiple bids have been placed). Theoptimal ad may be selected from a database containing multiple ads, suchas ads within an advertising campaign. The optimal ad may also containdynamically-created creative content, such as text or hyperlinks, whichtarget the intent of the user. In one example, the optimal ad is the adhaving the highest bid that exceeds the minimum bid. According to oneembodiment, if no ad has a bid that meets or exceeds the minimum bid, noad will be served. Notably, the minimum bid may serve as a thresholdthat should be exceeded to prevent the cannibalization of transactionrevenue that may occur if advertisements are displayed to the user. Inanother example, the optimal ad is the ad having the highest calculatedadvertisement revenue potential, which is also referred to as mediarevenue. Other exemplary ways of selecting an optimal ad are possible,including but not limited to selecting an ad offering a combination ofhighest bid and highest revenue potential.

The optimal ad, if any, is then delivered 120 to interface 101 anddisplayed to the user 122 within, for example, a web page produced bypublisher 102. According to another embodiment, more than one optimal admay be selected and displayed on the e-commerce website. An outcomeresulting from serving or not serving the optimal ad may be stored andused for future optimization of ad selection.

FIG. 2 illustrates various interactions of an exemplary system accordingto various embodiments of the disclosure. As shown, a publisher 200provides publisher content 200A, for example, one or more web pages eachhaving one or more advertisements, which may be viewed within a webbrowser operating on a client computer of a user (not shown). A mediaplatform 201 includes a system 201A for delivering advertising in anonline environment. System 201A includes, but is not limited to, anonline auction for providing access to publisher 200 from one or moreadvertisers 202. System 201A may also include one or more componentsadapted to identify and serve ads to publisher 200 to be displayed to avisitor viewing the web pages. Advertisers 202 provide one or moreadvertisements 202A and bids 202B to system 201A.

In one embodiment, system 201A determines and serves, based on bids202B, threshold criteria provided by advertiser 202, and user-generatedinformation from publisher 200, an optimal advertisement 202A to bedisplayed by publisher 200 within publisher content 200A.

In another embodiment, system 201A determines an intent of a userinteracting with publisher content 200A and serves, based on informationprovided by advertiser 202 and other information provided by publisher200, an advertisement 202A related to the intent to be displayed bypublisher 200 within publisher content 200A.

Exemplary System Architecture

FIG. 3 shows an architecture diagram of an example system 300 accordingto one embodiment of the invention. System 300 may, for instance, be oneimplementation of the system discussed above with reference to FIG. 2.It should be appreciated that FIG. 3 is used for illustration purposesonly, and that other architectures may also be used to facilitate one ormore aspects of the present invention.

As shown in FIG. 3, a distributed system 300 may be used to display oneor more advertisements to a user within an e-commerce site. According toone embodiment, system 300 may include one or more components thatoperate in cooperation with the e-commerce site. The components mayinclude one or more client systems 302 and a media system 304. Forexample, these components may execute on one or more computer systemsassociated with or interconnected to an e-commerce provider. System 300may include one or more processes that respond to requests from one ormore client programs, such as a web browser or agent-facing system(GDS). Process may include, for example, an HTTP server or otherserver-based process (e.g., a database server process, XML server,peer-to-peer process) that interfaces to one or more client programsdistributed among one or more client systems. One or more advertisers306 may interact with media system 304.

According to one embodiment, one or more client systems 302 may becapable of displaying advertisements to users. The client systems 302may include, for example, any type of operating system and/orapplication program capable of communicating with other computer systemsthrough a communication network, such as the Internet. In one particularinstance, the client system 302 may include a browser applicationprogram that communicates with one or more server processes using one ormore communication protocols (e.g., HTTP over a TCP/IP-based network,XML requests using HTTP through an Ajax client process, distributedobjects, etc.).

The client system 302 may include one or more interfaces 310 throughwhich advertisements may be presented to the user. In one example,advertisements may be presented in an interface of a browser programexecuting on a client computer system. As discussed above, one aspect ofthe present invention relates to determining a user's context and/orintent within an e-commerce site and using such intent and/or context todetermine ads displayed to a user. Such ads may be displayed, forexample, in an interface associated with an e-commerce site within aninterface of the browser program.

According to another embodiment, the media system 304 receives one ormore ad requests 312 from a publisher through the client system 302, andone or more advertiser inputs 314 from one or more advertisers 306. Themedia system 304 receives one or more advertisements and/or advertisingcampaigns from the advertiser 306, which are stored in an advertisingcampaign database 316. The media system 304 serves advertisements to thepublisher, which in turn displays the advertisement to a user through,for example, interface 310. The media system 304 includes the followingcomponents: a translation engine 320, a hurdle rate engine 322, acandidate list engine 324, an ad optimization engine 326, a decisionengine 328, and an outcome engine 330. The media system also includes,in addition to the advertising campaign database 316, a translationdatabase 332, a hurdle rate database 334, and an optimization database336.

As will be described in greater detail below, the translation engine 320translates the ad request 312 into one or more normalized values, suchas visitor intent or visitor process context. The candidate list engine324 generates, from the advertising campaign database 316, a list ofcandidate ads. A list of candidate ads may include one or more ads that,for example, target the intent of the visitor and/or target the visitorinteracting with an e-commerce website within a particular processcontext. For example, in an ad campaign for travel to multiple Caribbeandestinations, the list of candidate ads may contain ads, drawn from manyads in the campaign, for air travel to San Juan, P.R. if the visitorexpresses an intent to fly to Puerto Rico. In a further example, thelist of candidate ads may contain ads directed to hotels in San Juan ifthe visitor has purchased airline tickets to San Juan.

The hurdle rate engine 322 calculates a hurdle rate based at least onthe ad request, which may include information used to determine visitorintent, a request for one or more specific ad unit types, and otherinformation. The optimization engine 326 selects one or more optimal adsfrom the list of candidate ads having the highest potential mediarevenue and/or the highest associated bids. The decision engine 328selects any number of the optimal ads (including no optimal ads) and, ifany, serves them to the publisher for display to the visitor. Finally,the outcome engine 330 stores the outcome for future use. The outcomemay include, for example, the list of optimal ads and other dataassociated with the media system 304.

Exemplary Method

Shown in FIG. 4 is one embodiment of a process for deliveringadvertising 400. Process 400 may, for instance, be one implementation ofsystem 300 as discussed above with reference to FIG. 3. Process 400begins at start block 402. At block 404 an ad request is received from apublisher of an e-commerce website. The ad request may be received as aresult of user (also referred to as visitor) interaction with ane-commerce website. For example, a user performing a search at thewebsite may express an intent with respect to one or more products.Information based on the intent may be used by the publisher to generatean ad request, which is sent to a media system, such as media system 304referenced above with respect to FIG. 3. For example, a user searchingfor hotels in San Francisco may express an intention to visit SanFrancisco. This information may be included in the ad request, such asin a request for San Francisco hotel ads. The ad request may alsoinclude other information, such as a type of media ad unit requested bythe publisher.

At block 406 an ad request is translated by the media system. The adrequest may be translated into one or more intent targets and/or one ormore process contexts (also referred to as intent stages). Translationmay be performed, for example, by a translation engine 320 as discussedabove with reference to FIG. 3. For example, because informationincluded within the ad request may not be standardized, the ad requestmay be translated into a normalized set of values that facilitate anadvertisement bidding and selection process that is standardized acrossmultiple systems, advertising campaigns, and other cross-platform orcross-market activities.

At block 408, users may optionally be segmented into two or more groups.For example, one user may be designated as a “high value visitor,” andanother user may be designated a “low value visitor” based on a numberof factors including, but not limited to, whether the user is a pastpurchaser, a loyalty program member, or other factors that identify thevalue of the user to the publisher and/or advertiser. Other categoriesor classifications may be used to segment users. As described herein,according to one embodiment, user segmentation may be used to determinewhether an ad is displayed to the user; however, segmentation is notlimited to such use.

At block 410, a hurdle rate may be optionally calculated based at leaston the intent targets and/or process contexts of the user. According toone embodiment, the hurdle rate may be calculated by a hurdle rateengine 322 as discussed above with reference to FIG. 3. In oneembodiment, only user segmentation is performed. In another embodiment,only hurdle rate calculation is performed. In yet another embodiment,both user segmentation and hurdle rate calculation are performed.

At block 412, a list of candidate advertisements may be generated from aplurality of advertisements, such as advertisements within an adcampaign. The list of candidate advertisements may be generated by, forexample, a candidate ad list engine 324 as discussed above withreference to FIG. 3. In one embodiment, the list of candidate ads may begenerated based on the intent targets and/or process contexts.

At block 414, a list of candidate advertisements may be optimized. Inone embodiment, one or more ads from the list of candidate ads havingthe highest potential media revenue are selected by, for example, an adoptimization engine 326 as discussed above with reference to FIG. 3. Inanother embodiment, one or more ads from the list of candidate adshaving a bid greater than the hurdle rate are selected. Determination ofwhich candidate ads are selected may be based on specific orpre-selected user intents, or on other criteria set by publishers and/oradvertisers. For example, an advertiser may choose to only bid on adstargeting a specific intent, for example, an intent to travel toCalifornia by rail. In another example, a publisher may choose torequest ads that only target a specific intent.

At block 416, the selected ads are served to the publisher to bedisplayed to the user. At block 418, an outcome of serving the ad isstored. The outcome, for example, may include information about whetherthe ad was “clicked” on by the user, or whether the user completed atransaction on the website after the ad was displayed to the user. Forinstance, some users having similar intents (e.g., users expressing anintention to fly to San Juan) may be shown an ad, and other users havingsubstantially the same intents may not be shown any ad. The outcomesrelative to all users may be identified and stored for future use, suchas determining whether displaying the ad to the user created a negativeCPV, or a loss of net revenue or media revenue for the publisher. Such aloss of revenue may be caused, for example, by calculating a hurdle ratethat is too low, or by not properly segmenting users, or both. Otherfactors may also contribute to a loss of revenue, such as certainconfigurations of ad formats, ad uses, ad campaigns, and/or media unittypes.

At block 420, process 400 ends.

Visitor Intent

According to one aspect of the present disclosure, an intent of avisitor to an e-commerce website can be determined based on theinteraction of the user with the website. In one non-limiting example, avisitor searching for flights to Aruba is expressing an intention totravel to Aruba, which may be useful to an advertiser not only fordirected advertising of flights to Aruba, but for also advertising otherproducts related to the intent, such as hotels, restaurants, rentalcars, or other travel-related products. An intent of a visitor to ane-commerce website may represent a significant information asset held bythe publisher of the website, which may be monetized using variousembodiments of systems and methods disclosed herein.

In one embodiment of the disclosure, intent can be determined from thetype of website being visited, such as a travel planning website.However, this alone may not adequately describe the intent of thevisitor because, for example, the fact that the visitor is at a travelwebsite does not describe where, when, and how the visitor wishes totravel. To determine more information, intent can be determined based onkeywords or search terms supplied by the user, from behaviors of theuser as the user interacts with the website, such as selecting certainproduct descriptions and reviews, and/or from characteristics of theuser, such as a location of the user (e.g., New York, N.Y.) or a loyaltyprogram status of the user (e.g., the American Airlines AAdvantage Gold®loyalty program).

A publisher of an e-commerce website may realize transaction (or sales)revenue generated by a visitor when the visitor purchases a productthrough the website. The publisher may further (or alternately) realizemedia (or advertising) revenue when advertisements are displayed on webpages viewed by the visitor. It is appreciated that advertising targetedto the intent of the user may yield greater media revenue thannon-targeted advertising. Further, media revenue may further increase inproportion to a degree of targeting, for example, advertising targetedto a particular product within a class of products may yield higherrevenue than advertising targeted to the class of products. For example,ads for a class of products may include “flights to Honolulu,” and adsfor a particular product within the class may include “flights fromSacramento to Honolulu.” Accordingly, an intent of the visitor may beused to identify targeted ads of varying degrees which each represent aknown or expected level of revenue potential for the publisher.

Granularity of Intent

In another aspect, it is appreciated that by resolving an intent of avisitor to an e-commerce website into more granular specific intents,and allowing advertisers to bid on ads targeting the specific intents,the value of the ads in an auction-based market more accurately reflectstheir true market value. Commonly, for example, advertisers placebundled bids for a particular intent target, such as hotel rooms. In abundled bid, the same bid value is given to the hotel room adsregardless of how many nights the rooms are reserved for. Thus, thevalue of an ad for a hotel room is the same for a one-night stay as itis for a five-night stay. However, such bundled bids do not account forthe actual variation in values between ads targeting one-night stays andads targeting five-night stays. For example, an airport hotel, whichlargely caters to business travelers, accommodates guests for one-nightstays more frequently than five-night stays. Accordingly, ads targetingtravelers who intend to stay at an airport hotel for one night may havea higher value than ads targeting travelers who stay for five nights.

According to an embodiment, it is appreciated that bundled bids mayrestrict entrants into an advertising market because such bids do notaccount for differences in the value of a specific intent to eachadvertiser. For example, the value of an ad targeting a one-night stayat an airport hotel may be greater than the value of an ad targeting aone-night stay at a destination resort hotel (because fewer one-nightstays occur at a destination resort and therefore such ads are of lesservalue to the advertiser). Therefore, according to one embodiment,advertisers may bid on the opportunity to serve ads targeting a specificintent of an e-commerce website visitor. For example, advertisers mayplace separate bids for ads targeting a one-night hotel stay, two-nightstay, etc., based on characteristics of the hotel property (e.g.,airport, neighborhood, city, leisure/resort). By enabling advertisers tobid on more granular degrees of specific intent, the advertising marketfor advertisers may become more diverse and the value of the specificintent may more accurately reflect the true market value of advertisingthat is directed to the specific intent than advertising targeting amore general intent (e.g., bundled bids). Accordingly, differentadvertisers, each targeting a different specific intent, may beincentivized to bid for advertising a product (e.g., hotel rooms). Thehighest bid for each specific intent (e.g., one room-night) within thegeneral intent (e.g., hotels), may therefore be placed by differentadvertisers.

Intent Stage

According to one aspect of the disclosure, an intent of a visitor may beassociated with an intent stage (or process context). The intent stagemay be used to identify a position of the visitor in the“shopping-purchase-consumption” process. Further, the intent stage maybe used to associate the position (or context) of the visitor with oneor more relevant advertisements. For example, a visitor beginning asearch for a product may have an intent stage of “shopping.” A visitorwho is “shopping” may continue to shop, or may discontinue shoppingwithout making a purchase (e.g., “bailing-out”). During the shoppingstage, the visitor may be searching for a product, viewing a list ofproducts, viewing details of one or more selected products, or placingone or more selected products into a “shopping cart” for purchase. Eachof these activities may be used to provide additional information aboutthe visitor.

An example of an ad relevant to “shopping” is an ad served on any pageviewable during the shopping process or within an “alert e-mail.” Anexample of an ad relevant to “bailing-out” is an ad served within a“pop-under” window, which is displayed to the visitor after leaving thewebsite. In another example, a visitor who has completed a purchasetransaction may have an intent stage of “post-purchase” or“consumption.” An example of an ad relevant to “post-purchase” or“consumption” is an ad on a purchase confirmation web page, or an ad ona post-purchase confirmation or follow-up e-mail.

In one embodiment, an intent stage may be used to determine an optimaladvertisement to be displayed to a visitor. As discussed below, theintent stage may alter the hurdle rate or minimum bid price for an ad.For example, a hurdle rate may be lower for a visitor who has completeda purchase relative to a visitor who is still shopping because, after atransaction, the publisher has acquired transaction revenue and thus theCPV could only increase by also receiving media revenue. In anotherexample, a hurdle rate may increase as a visitor achieves a deeperintent stage (e.g., an ad on a second page of the website may be morevaluable to the advertiser than an ad on a first page of the websitebecause the intent of the visitor may be more specifically determined asthe visitor continues to interact with the website).

Media Unit Types

According to an aspect, various embodiments of systems and methodsdisclosed herein will accommodate a variety of advertising types. Amedia unit type, as used herein, refers to a form of advertising formonetizing intent. In one embodiment, the media unit type is a standardad unit. A standard ad unit includes an Interactive Advertising Bureau(IAB) standard ad slot on a web page provided by a publisher where thecreative content of the ad is provided by the advertiser.

In another embodiment, a media unit type is an integrated ad unit. Anintegrated ad unit is a non-IAB standard ad slot on a web page providedby a publisher where the ad contains publisher-specific style, form,and/or content.

In still another embodiment, a media unit type is a comparison shoppingwidget. A comparison shopping widget is an interface that allows avisitor to perform a single search that matches the intent of the useracross multiple retailers or merchants. For example, a box is displayedcontaining multiple retailer names and check boxes next to each name. Ifthe visitor selects any check box, the search will be performed for eachof the selected retailers, and the results are then returned to thevisitor. The results may be displayed to the visitor on the same or adifferent webpage.

In yet another embodiment, a media unit type is an e-mail containing anad.

Click Models

According to an aspect, various embodiments of systems and methodsdisclosed herein accommodate a variety of “landing page” models. Alanding page is a web page that is displayed when a user clicks on anad. For example, if a user clicks on an ad for flat screen TVs, the usermay be presented with a new web page listing flat screen TVs for sale. A“click-out” ad is an advertisement that links the user to a landing pagespecified by the advertiser (e.g., a web page on the advertiser'swebsite).

A “click-in” ad is an ad that links the user to a landing page withinthe publisher's website, for example, where an advertiser pays forplacing an ad on the publisher's website. The content (or creativecontent) of the click-in ad may be provided by the publisher and/or theadvertiser.

Relevance Types

According to another aspect, visitor intent at an e-commerce website isassociated with one or more relevance types. A relevance type describesa benefit enjoyed by the visitor that may be derived from receiving anadvertisement that is targeted to the specific intent of the visitor.The relevance type defines a relationship between the ad and an intendedtarget of the ad. Each ad may have one or more relevance typesassociated to it.

As will be discussed in further detail below, there may be multiplerelevance types including, but not limited to, retailer discovery,substitute discovery, and complement discovery. It should be understoodthat these relevance types are merely exemplary and that other types arealso possible.

In one embodiment, visitor intent may be associated with a relevancetype of retailer discovery. Retailer discovery is relevant to the intentwhere an ad provides information about one or more retailers where theintent can be satisfied (e.g., retailers of a specific product orrelated product). For example, if the intent of the visitor is topurchase a Samsung LCD TV, an ad stating “Shop Samsung TVs atnewegg.com” may be relevant to the intent because it enables the visitorto discover a retailer that can satisfy the intent.

In another embodiment, visitor intent may be associated with a relevancetype of substitute discovery. Substitute discovery is relevant to theintent where an ad provides information about other products that mayalso satisfy the intent (e.g., similar and/or comparable products thatare sold by other retailers). For example, as above, if the intent is topurchase a Samsung LCD TV, an ad stating “Sony TVs have the clearestpicture” or “Sale on plasma TVs” may be relevant to the intent becauseit enables the visitor to discover substitute brands or products thatcan satisfy the intent.

In yet another embodiment, visitor intent may be associated with arelevance type of complement discovery. Complement discovery is relevantto the intent where an ad provides information about products thatcomplement the intent (e.g., accessories, product-related services). Forexample, as above, if the intent is to purchase a Samsung LCD TV, an adstating “Fast and reliable TV home installation services” or “Blu-RayDisc players” may be relevant to the intent because it enables thevisitor to discover services and/or products that are complementary tothe intent.

In one embodiment, one or more ads are associated with a relevance typebased on an intent or based on the content of a web page. The publishermay choose one or more of the relevance types to control or limit whichtypes of ads are displayed on their website. For example, the publishermay choose to display only ads having a relevance type of complementdiscovery.

In another embodiment, a relevance type is associated with an intentdynamically, for example, by the media platform. For example, the mediaplatform may associate an ad to one or more relevance types based onknown or predicted relationships.

As discussed above, more than one relevance type may be appropriate foran ad. In one example, an electronics retailer is advertising a Blu-Raydisc player. If the intent of a visitor is to purchase a flat screen TV,then the ad may be relevant for complement discovery because the discplayer is commonly purchased in conjunction with the TV, and because thedisc player can be purchased from the electronics retailer. If theintent of the visitor is to purchase a Blu-Ray disc player, then the admay be relevant for retailer discovery because the disc player can bepurchased from the electronics retailer. If the intent of the visitor isto purchase a Samsung Blu-Ray disc player (i.e., a specific product),then the ad may be relevant for substitute discovery because anotherbrand of disc player can be purchased from the electronics retailer.

In another example, a restaurant is advertising itself. If the intent ofa visitor is to reserve a hotel room in New York, the ad may be relevantfor complement discovery because the restaurant is in New York (or nearthe hotel) and the visitor will likely be dining out while staying atthe hotel. If the intent is to purchase airline tickets to New York, thead may also be relevant for complement discovery because the visitor islikely to be dining out after flying to New York. If the intent is tolocate restaurants in New York, the ad is relevant for retailerdiscovery because the ad is for a restaurant. If the intent is to locatea steakhouse in New York, the ad may be relevant for substitutediscovery if the restaurant serves steak, but is not a traditionalsteakhouse.

In one embodiment, a relevance type of an ad is assigned by anadvertiser. In another embodiment, a relevance type of an ad isautomatically or semi-automatically assigned. Such automatic orsemi-automatic assignments may be facilitated at least in part by therelevance type assigned to the ad by the advertiser. For example, adatabase including mappings between types (or classes) of advertisementsand normalized intent targets may be used to assign a relevance type toan ad based on the intent of a visitor. The mappings may be created ormodified based on the manual assignment of a relevance type to an ad by,for example, an advertiser.

Translation

According to one aspect, it is appreciated that advertising may target aspecific intent of a website visitor, as opposed to targeting moregeneral characteristics of the visitor or the products that the visitoris searching for. Targeted advertising may be enabled by translating asearch performed by the visitor (or from other information received fromthe visitor) into an intent target that is normalized across a verticale-commerce market. Such normalization facilitates the ability to servetargeted ads to multiple publishers because each publisher may utilizediverse nomenclature in describing visitor intent.

In one embodiment, a publisher solicits advertising from one or moreadvertisers by providing data representing a context of a visitor to ane-commerce website that is published by the publisher. The context mayinclude an intent of the visitor, or information from which the intentmay be determined. The context may also include an intent stage (orprocess context) of the visitor, which relates to the interaction of thevisitor to the e-commerce website, as described below. The context isthen parsed and translated or normalized into a common taxonomy that isapplicable across multiple advertisers operating within, for example, avertical market (e.g., travel: flights, hotels, rental cars, etc.). Thenormalized data may represent a specific intent of the visitor that maybe used to identify relevant advertisements that target the intent. Forexample, if the intent of the visitor is to purchase airline ticketsfrom Dallas/Fort Worth to Chicago, departing on Jan. 13, 2009 andreturning on Jan. 20, 2009, the data representing this intent may benormalized as {ORIGIN=DFW; DESTINATION=ORD; DEPART=01-13-09;RETURN=01-20-09}. Such normalized intent data facilitates theidentification of ads relevant to the intent across multiple publishersand/or advertisers, for example, ads for airline tickets thatspecifically target the desired itinerary of the visitor.

In another embodiment, visitor intent is represented by one or morekeywords.

For example, a visitor entering “flights from Boston to Miami” isexpressing an intent to locate flights from Boston to Miami. Thesekeywords may be translated into normalized intent data as describedabove, for example, {MODE=AIR; ORIGIN=BOS; DESTINATION=MIA}.

According to one embodiment, when a visitor visits an e-commercewebsite, an ad request is provided by a publisher of the website to atranslation engine. The ad request may contain, for example, one or morekeywords or search terms supplied by the visitor. The translation engineparses the ad request into one or more normalized attributes and/orvalues, and translates the normalized attributes/values into an intenttarget. The intent target may then be used to generate one or moresynonymous intent targets. The intent target and/or synonymous intenttargets may be used, for example, to identify, from among a group ofadvertisements, one or more candidate advertisements to be displayed tothe visitor.

In another embodiment, an ad request provided by a publisher containsone or more variables representing one or more aspects of visitorintent, such as keywords or search terms provided by the visitor. Thetranslation engine parses the attributes and/or values of each variableinto one or more normalized attributes or values. For example, in afirst travel service website, one variable may have the attribute of“ORIG” to represent the visitor's city of origin, and in a second travelservice website, one variable may have the attribute of “DEP” torepresent the same departure city. Each of these attributes, and others,may be parsed into a normalized attribute of “ORIGIN,” which indicatesthat the corresponding value of the variable represents the visitor'scity of origin. In another example, a variable may have the value of“BOS” (IATA airport code), “KBOS” (ICAO airport code), “Boston” (airportcity name), or “Logan International Airport” (airport name). Each ofthese values may be parsed, for example, into a normalized value of“BOS,” which indicates that the value represents Boston's Logan Airport.In this manner, the intent is normalized across all publishersregardless of the form of the variable attribute as received from thepublisher, which may vary from one publisher to another.

In another embodiment, an ad request provided by a publisher containsone or more variables representing a process context of a visitor, suchas a URL indicating where the visitor is interacting within thee-commerce website. A translation engine parses the context into anormalized value. For example, the URL, when parsed, may provideinformation about the visitor's activity on the website, such as whetherthe visitor is searching for a product (e.g., locating and/orresearching the product), selecting the product (e.g., placing theproduct into a “shopping cart”), or purchasing the product (e.g.,“checking-out”). The URL, or components thereof, may be parsed into anormalized context representing the visitor's context, such as“SHOPPING,” “SELECTING,” or “PURCHASED.” In this manner, the visitor'scontext is normalized across all publishers regardless of the form ofthe URL received from the publisher, which may vary from one publisherto another.

According to another aspect of the disclosure, a translation enginetranslates a structured advertising campaign into one or more keywordcampaigns. The keyword campaigns may contain normalized keywords. Thekeyword campaign translation facilitates serving ads drawn from an adcampaign, which target a specific intent, to visitors having thespecific intent by matching the intent to certain keywords. Thosekeywords may be mapped to respective ads in the ad campaign. Forexample, an electronics retailer may submit to, for example, a mediasystem 300 as discussed above with reference to FIG. 3, an advertisingcampaign featuring a particular model of Sony televisions. Thetranslation engine of media system 300 converts the advertising campaigninto one or more keywords relevant to the television model beingadvertised, such as screen size, screen type, and bezel color. Thekeywords may then be used, for example, matching an intent of a visitorto the advertising campaign. For example, if the visitor enters one ormore of the relevant keywords, an advertisement request including thekeywords may cause an ad from the ad campaign (e.g., an ad for theparticular television model) to be displayed to the visitor.

Segmentation

According to one aspect, visitors to an e-commerce website are segmentedinto multiple groups. In one embodiment, segmentation may be used toidentify a relationship between a user and a publisher of a website. Inone non-limiting example, a user may be a visitor having low value tothe publisher, that is, a visitor who is expected to generate little tono net transaction revenue or advertising revenue for the publisher, andtherefore has a low value to the publisher. In another example, a usermay be a loyalty program member who has a high value to the publisher.Segmentation of visitors may be used to facilitate a decision as towhether an advertisement is served to a particular visitor. Segmentationmay be used in conjunction with a hurdle rate calculation (described infurther detail below) or alone.

In one embodiment, visitors are segmented into two groups: high valuevisitors (HVV) and low value visitors (LVV). Information regardingvisitors may be supplied by the publisher. The value of the visitor isdefined with respect to the publisher. For example, a HVV may be avisitor who is likely to complete a transaction with the publisher if noad is served. A LVV, on the other hand, may be a visitor that is lesslikely to complete a transaction with the publisher than a HVV is. Inanother example, a HVV may be a visitor who has previously made apurchase at the website or from the merchant (intent), a registered userof the website (status), or a loyalty program member (status). A LVV maybe a visitor who is not a HVV. A LVV, for example, is a visitor whoexpresses an intent to locate a product but is likely to leave thewebsite without purchasing the product. It should be understood thatthese groupings are exemplary and that other or additional groupings arepossible.

In another embodiment, no ads are displayed to a HVV because thepotential risk of cannibalizing revenue from the HVV is high if an ad isdisplayed, or the risk is at least above a predetermined threshold setby the publisher. This risk threshold may be, according to oneembodiment, included in a determination of whether the visitor is a HVV.

In yet another embodiment, segmentation may be based on known and/oravailable information about a visitor. Such information may includeinformation provided by a publisher regarding the visitor, such aswhether the visitor is a past purchaser or a loyalty program member.Other information may be defined and/or provided by the publisher thatmay be used for segmentation. Segmentation may be based on informationthat includes, but is not limited to, intent variables (e.g., search orpurchase data), user variables (e.g., user status), media unit type(e.g., standard ad unit, integrated ad unit, comparison shopping widget,e-mail, pop-up or pop-under window), analytics hooks (e.g., pixeling orscripting), process context mapping (e.g., location of user withinprocess), intent mapping (e.g., normalized intent), hurdle rate,exclusions, and other data.

In another embodiment, segmentation may be based on historical dataprovided by a publisher and/or collected by another source. Suchinformation may include, for example, sales trends for one or moreproducts, conversion rates (completed transactions versus uncompletedtransactions), or other data relevant to the intent, behavior, and/orcharacteristics of a visitor.

In another embodiment, segmentation may be based on informationcollected by a source other than the publisher. In one example, thesource may place a “pixel” (or hook) on one or more web pages of thepublisher. The pixel is linked to a program (or script) that collectsinformation about a visitor. The collected information may be used, forexample, to create a model that describes the intent, behavior, and/orcharacteristics of one or more visitors to a particular website or webpage for segmentation purposes. The data may be collected from aDocument Object Model (DOM) of the web page containing the pixel, orfrom cookies stored on a client system.

In another embodiment, segmentation may be based on one or more of thefollowing: product; product category; media unit; relevance type;historical behavior, where such behavior includes past purchase history,browsing history, user preferences, demographics, and/or usercharacteristics; real-time visitor behavior and/or characteristics,where such behavior and/or characteristics includes browsing activity,traffic source (e.g., affiliate, bookmark, paid or organic search,comparison shopping engine, and/or outbound CRM), time of day, day ofweek, month and/or year, intent stage (e.g., shopping, browsing,bailing-out, post-purchase, and/or post-consumption); and visitorintent. Segmentation of visitors may also be based on visitor behavioracross multiple publishers, for example, whether a visitor uses onewebsite to search for a product (e.g., a travel search engine such asthe Kayak.com® search engine to locate flights) and another website topurchase the product (e.g., the AA.com® website by American Airlines).

According to another embodiment, segmentation may be combined with arelevance type associated with an intent of the visitor to identify, fora particular ad, whether the visitor is a HVV or a LVV. For example, avisitor who has previously purchased from a website that sells workboots may be classified as a HVV where the intent is to purchase workboots, the relevance type is retailer discovery, and the ad is foranother website that sells work boots. If no ad is served to thisvisitor, there is a greater chance that the visitor will purchase workboots from the website and not from another source because the visitorwill not discover alternate retailers or products through advertising atthe website. In another example, the same visitor may be classified as aLVV where the intent is to purchase work boots, the relevance type iscomplement discovery, and the ad is for rain gear, because the visitorhas no history of purchasing rain gear from the website and thereforethere is a lesser chance that the visitor will make such a purchase.

Hurdle Rate

According to one aspect, it is appreciated that a publisher of ane-commerce website may be reluctant to serve an ad to a visitor if thead has the potential to cannibalize the expected transaction revenuereceived from the visitor. For example, a publisher that sells widgetsmay be unlikely to serve ads for a competitor that also sells widgets,particularly where the competitor offers to sell the widget for lessthan the publisher. However, it is also appreciated that many visitorsto the website are unlikely to make a purchase, and as such thepublisher receives no transaction revenue from those visitors whether ornot an ad is displayed. Therefore, in an instance where the value of theintent (e.g., the potential media revenue received for an ad targetingthe intent) can be determined, the expected transaction revenue avisitor may serve as a basis for determining a hurdle (or threshold)rate. The hurdle rate represents an optimum minimum bid price or minimumcombination of bid prices by one or more advertisers for serving an ad,which may be generated in real-time, below which no ad will be served tothe visitor.

In one embodiment, a hurdle rate represents a price that is at least asgreat as the expected transaction revenue received from a visitor who isnot served an ad. For example, many visitors to an e-commerce websitemay shop for airline fares between two cities, but relatively few of thevisitors will complete a purchase during their visit. An advertisementthat does not target the intent of the visitor may be of lesser value tothe advertiser than a targeted ad because there is a lesser chance thatthe ad will lead to a transaction with the advertiser. On the otherhand, highly targeted ads, based on intent, may represent a high valueto the advertiser, but also a high risk to the publisher serving the adbecause the ad is more likely to draw the visitor away from thepublisher and toward the advertiser before the visitor completes atransaction with the publisher. Accordingly, the hurdle rate mayrepresent an optimal balance between transaction and media revenue for aparticular visitor, allowing the publisher to monetize the value of theintent where the expected transaction revenue from the visitor is lessthan the potential media revenue acquired from serving the ad.

In another embodiment, a hurdle rate is based at least in part on anintent and/or intent stage (or process context). The intent stageincludes shopping (e.g., viewing a product browse page, search resultspage, product list page, product detail page, and/or an e-mail, or wherethe visitor has “bailed-out” or exited the website) and post-purchase(e.g., transaction confirmation or follow-up). As described above, thehurdle rate reflects a price at which potential media revenue meets orexceeds the expected transaction revenue from a visitor. In turn, theexpected transaction revenue may be determined based on the visitor'sintent or intent stage. For example, for a visitor who is merelybrowsing products at the website, the expected transaction revenue maybe low because it is uncertain if the visitor will complete a purchaseof any product. However, once the visitor narrows his or her search to aparticular product (or products), confidence may increase that atransaction will occur, and thus the expected transaction revenue forthe visitor may increase. If the visitor begins the transaction process,the expected transaction revenue again increases. Therefore, the hurdlerate increases as the expected transaction revenue increases.

According to one embodiment, a hurdle rate is calculated based on one ormore of the following data: product cost, product price, product value,number and quality of visitors, number of sellers, historical averageconversion rate for a particular intent target, average contributionmargin for a completed transaction for a particular intent target,adjustment rules for each user segment and/or behavior, adjustment rulesfor one or more intent stages, publisher input (e.g., preferences,knowledge, capability), product inventory, or other data. For example,the data may be acquired from the publisher or another source. Inanother example, the data (e.g., conversion and/or contribution data)may be acquired through an analytics hook, such as a “pixel” on thepublisher's website.

In one embodiment, a hurdle rate is based on an expected transactionrevenue where no ad is served to a visitor less an expected transactionrevenue where an ad is served to the visitor. For example, if theexpected transaction value where no ad is served is $14 and the expectedtransaction value where an ad is served is $9, the hurdle rate is $5.The hurdle rate may establish the minimum value of an ad for a givenintent target and/or context target. Ads having bids below the hurdlerate will not be served.

In another embodiment, a hurdle rate is the minimum amount of mediarevenue a publisher must receive to offset an expected loss in revenuefrom transactions (e.g., transactions occurring with others than thepublisher) or other media (e.g., advertisements). For example, in amulti-click ad unit (described in further detail below), multipleadvertisers may be bidding for placement of ads within an individual adunit (e.g., a comparison shopping widget having two or more advertisersproviding advertising based on a common set of attributes, such asintent, keywords, or other visitor-supplied search terms). In thisexample, the total of all bids received must exceed the hurdle ratebefore an ad is served. Accordingly, one or more of the bids may be lessthan the hurdle rate for certain ad units (e.g., a multi-click unit oran ad unit having multiple advertising spots); however, all of the adsin the ad unit will be served if the combined bids exceed the hurdlerate for the ad unit.

In yet another embodiment, adjustments to the hurdle rate may beapplied. For example, the hurdle rate may be adjusted upward or downwardbased on a status of the visitor (e.g., loyalty program member, returnvisitor, registered visitor, or other status) and/or a process contextof the visitor (e.g., visitor is on home page, product list page,product details page, or other page). A hurdle rate formula may beexpressed, for example, as:

Hurdle rate=(average conversion rate)*(segmentation/behavior conversionadjustment)*(intent state conversion adjustment)*(average contributionmargin)*(segmentation/behavior contribution margin adjustment)*(intentstate contribution margin adjustment)

It should be understood that the above formula is exemplary, and thatone or more variables may be added, modified, or deleted.

In another embodiment, a hurdle rate may be based on other rates, suchas a publisher-calculated rate or a publisher-calculated adjustmentrate.

In one embodiment, a hurdle rate is calculated by the media platform,such as media platform 201 as discussed above with reference to FIG. 2.The calculation may include data provided by the publisher, the mediaplatform, and/or another source. In another embodiment, the hurdle rateis provided to the media platform by the publisher. The hurdle rate maybe the higher (or lower) of the publisher-provided hurdle rate and thecalculated hurdle rate. In yet another embodiment, a hurdle rateadjustment is provided by the publisher and incorporated into the hurdlerate calculation.

In yet another embodiment, a hurdle rate may include an adjustment to“boost” the hurdle rate. The adjustment may be a numerical adjustment ora percentage-wise adjustment.

In still another embodiment, a hurdle rate may be based on a returnrate. The return rate represents the percentage of visitors to a firstwebsite who return to the first website after following an ad viewed onthe first website which directed the visitor to a second website (e.g.,an advertiser's website). The returning visitor may or may not completea transaction at the first website. For example, the return rate mayrepresent a “return to visit” rate or a “return to purchase rate.” Areturn to visit rate is the rate at which a visitor returns to visit thefirst website after leaving the first website to visit another site(e.g., by clicking on an ad), but subsequently makes no purchase at thefirst website. A return to purchased rate is the rate at which a visitorreturns to purchase a product from the first website after leaving thefirst website.

According to another embodiment, a hurdle rate represents the fullyloaded expected value (FLEV) associated with the intent of a visitor.The FLEV is based on the expected media value of an ad in addition tothe expected return transaction value (e.g., the value of a transactioncompleted by a visitor returning to a first website after following anad to a second website). The net FLEV may be expressed, for example, asan expected contribution per visitor value less a revenue share valueplus a return transaction value.

FIG. 5 illustrates an exemplary process for calculating a hurdle rate500 in accordance with one embodiment. At block 502, process 500 begins.At block 504, a base conversion and adjustments for one or more intenttargets and/or process contexts are retrieved. The base conversionand/or adjustments may be retrieved, for example, from a database, suchas a hurdle rate database.

According to one embodiment, a base conversion may be based on an intenttarget. For example, if the intent target is hotels in Dallas, the baseconversion may be 2%. The base conversion may be based on a processcontext. For example, if the intent is hotels in Dallas, and the processcontext is “SHOPPING”, the base conversion may be 2.75%. It will beunderstood that the conversion values are exemplary and that any valuesmay be used.

According to another embodiment, an adjustment may be based on acharacteristic of a visitor. For example, a registered user adjustmentmay be 300%. In the above example, the base conversion would be adjustedupward by 300% if the user is a registered user.

At block 506, an adjusted conversion rate is calculated based on thebase conversion and adjustments, as described above.

At block 508, a variable contribution is retrieved. The variablecontribution may be retrieved, for example, from a database, such as ahurdle rate database. In one example, the variable contribution is afixed dollar amount that is contributed by the advertiser to the hurdlerate. It will be understood that other forms of variable contributionare possible.

At block 510, a hurdle rate is calculated. For example, the hurdle ratemay be calculated as the adjusted conversion rate multiplied by thevariable contribution.

At block 512, an adjusted hurdle rate is optionally calculated. Forexample, the hurdle rate may be adjusted to account for revenue sharingby a third party (e.g., the hurdle rate may be increased to cover theamount of revenue to be shared with the third party).

At block 514, process 500 ends.

Candidate List

According to an aspect, a candidate advertisement list is generated by acandidate list engine. The candidate advertisement list includes one ormore ads that are selected from a group of ads, for example, ads in anadvertising campaign, and that meet certain criteria, for example, adsthat target an intent and/or ads having bids that exceed a hurdle rate.The ads in the list include ads that are candidates for display to thevisitor based on at least some of the criteria.

The candidate list engine is connected to one or more ad campaigndatabases. An ad campaign may include one or more of the following:dates (e.g., dates for which the campaign is valid or active), deliveryrules, budget, bid groups, placement targets, intent targets, and/or adcreatives (e.g., ad content). The candidate advertisement list includesone or more advertisements selected from the one or more ad campaigndatabases.

FIG. 6A illustrates an exemplary process for generating a list ofcandidate advertisements 600. Process 600 begins at block 602. At block604, a candidate list engine receives one or more variables eachrepresenting one or more of the following: an intent target, a processcontext, an ad unit identifier, one or more ad unit attributes, apublisher name, a cookie, and a hurdle rate. The intent may be anormalized intent. The variables may be received from a database, forexample, an ad campaign database.

At block 608, the engine retrieves, from the database, one or moreactive ad campaigns where the bid is greater than the hurdle rate. Thead campaigns may include one or more advertisements and otherinformation related to the ads, such as bids, dates, rules, and/orcreative content.

At block 610, a first filter is applied. The first filter acts todisqualify one or more ads based on one or more rules. The rules, forexample, may include exclusions, ad delivery limitations, and/oreligibility requirements. Other rules may be applied.

At block 612, the engine retrieves, from the database, one or more adunit attributes. The ad unit attributes may include a media unit type ofthe ads, for example, a standard ad unit, an integrated ad unit, acomparison shopping widget, or an e-mail.

At block 614, a second filter may be applied. The second filter acts todisqualify one or more ads based on one or more ad unit attributes,where the ads do not match the ad unit attributes. Ad unit attributesmay describe, for example, the format (e.g., size, style, etc.) of thead. For example, if the publisher requests only integrated ad units,then ads that are not integrated ad units will be disqualified.

At block 616, a third filter may be applied. The third filter acts todisqualify one or more ads based on the intent. For example, if the addoes not target the intent, it may be disqualified. Alternatively, if noads target the intent, the third filter may be relaxed. For example, ifthe intent is specific, such as “flights between 5:00 PM and 8:00 PM,”and no ads match the intent, then the third filter may be relaxed toallow ads targeting “flights between noon and midnight” to pass throughthe filter. This prevents the list of candidate ads from becomingeviscerated by specific intents.

At block 618, a fourth filter may be applied. The fourth filter acts todisqualify one or more ads based on the process context. In one example,the process context represents a normalized context of a visitor, asdescribed above, such as “SHOPPING,” “SELECTING,” or “PURCHASED.” If thead does not match the process context, it may be disqualified.Alternatively, if no ads match the process context, then the fourthfilter may be relaxed. For example, if the process context is later intime, such as “PURCHASED,” then the fourth filter may be relaxed toallow ads targeting a process context of “SHOPPING” and/or “SELECTING”to pass through the filter. In one embodiment, the filter is relaxed toinclude one or more prior process contexts, that is, to include anyprocess context that is earlier in time than the current processcontext. This prevents the list of candidate ads from becomingeviscerated by process contexts that are later in the process.

At block 620, a list of candidate ads is generated. The list of ads mayinclude one or more ads that are not disqualified. If the list ofcandidate ads contains no ads, then no ad is displayed to the visitor.Otherwise, the list of candidate ads may be passed to an ad optimizationengine, which is described below. Process 600 ends at block 622.

FIG. 6B illustrates another exemplary process for generating a list ofcandidate ads 650. Process 650 begins at block 652. At block 654, acandidate list engine receives one or more variables each representingone or more of the following: an intent of a visitor, a process context,an ad unit identifier, one or more ad unit attributes, a publisher name,a cookie, and a hurdle rate. The intent may be a normalized intenttarget and/or normalized process context.

At block 656, the engine retrieves, from the databases, one or moreactive ad campaigns. The ad campaigns may include bids, rules, and/ormedia unit types associated with each of the ads. At block 658, theengine selects, from the active ad campaigns, one or more ads where thebid exceeds the hurdle rate. At block 660, the engine further selectsone or more ads that meet one or more rules, where the rules may defineone or more criteria related to the ad campaign.

At block 662, the engine further selects one or more ads that match theone or more ad unit attributes. At block 664, the engine further selectsone or more ads that match the intent. At block 666, the engine furtherselects one ore more ads that match the process context.

At block 668, a list of candidate ads is generated. The list of ads mayinclude one or more of the selected ads. If the list of candidate adscontains no ads, then no ad is displayed to the visitor. Otherwise, thelist of candidate ads may be passed to an ad optimization engine, whichis described below. Process 650 ends at block 670.

Ad Optimization

FIG. 7 illustrates an exemplary process for optimizing ad selection 700.One or more ads within a list of candidate ads may possesscharacteristics that may provide for an optimal CPV. Non-limitingexamples of ads that may have an optimal CPV include ads having thehighest bids, ads selected for display to a low value visitor, adsselected for display to visitors having a low expected return topurchase value, and other factors that may be based on historical data.In one non-limiting example, an expected return to purchase value may bea value that is assigned to a visitor based on the likelihood that thevisitor will, after viewing an advertisement on a website, return to thewebsite to complete a transaction. If the visitor is unlikely to returnto purchase, then the expected return to purchase value may increase asa result of the diminished likelihood that the visitor will complete atransaction at the website if an ad is displayed to the visitor.Accordingly, there will be no transaction revenue received from thevisitor if displaying an ad causes the visitor to leave the websitewithout purchasing anything. Therefore, a higher expected return topurchase value may allow the publisher of the website to recover anypotential loss in transaction revenue resulting from displaying an ad bysetting a hurdle rate (or minimum bid) at least as high as the potentialloss in transaction revenue. Thus, according to one embodiment, a hurdlerate calculation may be based on the expected return to purchase valueof a visitor to a website.

As shown in FIG. 7, process 700 begins at block 702. At block 704, an adoptimization engine receives one or more of the following from adatabase: a list of candidate ads, a hurdle rate, and one or more bids,each bid associated with one of the ads in the list of candidate ads.The optimization engine selects, from the list of candidate ads, one ormore optimal ads each having the highest revenue potential and/or thehighest associated bid. In one example, the optimization enginedetermines a value for each ad in the list of candidate ads, assigns arank to each ad, and provides one or more of the ads to a decisionengine (described below).

At block 706, the ad optimization engine retrieves, from a database, ahistorical CTR for each ad and/or advertiser in the list of candidateads. At block 708, the ad optimization engine retrieves, from thedatabase, a historical return rate for each ad and/or advertiser in thelist of candidate ads. At block 710, the ad optimization engineretrieves, from the database, an expected transaction value.

At block 712, the ad optimization engine calculates a return value. Thereturn value may be, for example, calculated as the expected transactionvalue times the return rate.

At block 714, the ad optimization engine calculates a revenue potentialvalue for each ad in the list of candidate ads. The revenue potentialvalue may be, for example, calculated as the bid times the CTR,increased by the return value.

At block 716, the ad optimization engine selects one or more ads havingthe highest revenue potential. Process 700 ends at block 718.

In another embodiment, the ad optimization engine selects one or moreads based on a natural search position of the visitor, for example, aprocess context. For example, if the process context is “purchased,” adsthat are relevant to complement discovery may be more optimal than adsthat are relevant to retailer discovery because the former possesses agreater value to the publisher than the latter.

In another embodiment, the ad optimization engine generates, for an adin the list of candidate ads, a link to a web page. The link may beincluded with the ad, for example, as a hyperlink embedded in the ad.The link may be dynamically generated based, for example, on intent orother information, to lead a visitor to a targeted ad located on the webpage.

Ad Decision

According to an aspect, an ad decision engine receives one or more adshaving the highest revenue potential and/or a bid rate exceeding thehurdle rate. In one embodiment, if any of the ads having the highestrevenue potential meet or exceed the hurdle rate, one or more of the adshaving the highest revenue potential are served to a publisher fordisplay to a visitor.

Exemplary System

FIG. 8 illustrates one embodiment of a system 800 that is capable ofdelivering advertising according to various embodiments of the presentdisclosure. As shown, system 800 may include one or more components thatperform one or more functions. These components can be arranged in otherconfigurations and groupings, and other configurations and groupings maybe possible. According to one embodiment, system 800 includes areal-time system 801 including one or more components that performvarious functions in real-time. For instance, real-time system 801 mayinclude an HTTP/HTTPS listener, an event handler that is capable ofhandling events relating to the handling of advertisements, loggingcomponent that logs information and events, among others. Notably,system 801 may include components that perform hurdle rate calculations,matching of advertisements, and/or translation into context/intenttargets as discussed above.

System 800 may also include other components, including, but not limitedto a historical data store 802 that includes historical informationrelating to the serving of advertisements in relation to determinedintent of a user. System 800 may also include a component 803 thathandles billing and payment functions. System 800 may also include acomponent 804 that performs optimization functions to permit theoptimization of a particular internet publisher's profit. Further,system 800 may also include, for the benefit of a publisher, advertiser,or system administrator, a number of reports that relate to thefunctions and performance of system 800.

System 800 may also include an operational data store 806 that isadapted to store configuration information and data used by system 800.Store 806 may be coupled to one or more components that use store 806 tomanage data. System 800 may also include a number of other componentsthat permit a publisher, an advertiser, or system administrator toperform various functions within system 800. Such components may beconfigured using one or more interfaces configurable through anExtranet, Intranet, Internet, or Application Program Interface (API).

For instance, some administrative functions that may be performedinclude the administration of groups, management of taxonomy, relevancetype creation and mapping, and/or monitoring and control of system 800using an operational dashboard or other control type. Some publisherfunctions that may be performed may include inventory management,consumer segment management, hurdle rate management, translation mappingmanagement, and advertising feed management. Some advertiser servicesthat may be performed include campaign management, campaign mapping,and/or creative management.

Comparison Shopping Widget

In an embodiment, the media unit type (ad type) is a comparison shoppingwidget (also referred to herein as a multi-click ad unit). A comparisonshopping widget is an interface that allows a visitor to perform asingle search that matches the intent of the user or other searchcriteria across multiple retailers or merchants. For example, a box isdisplayed containing multiple advertiser names and check boxes next toeach name. If the visitor selects any check box, the search will beperformed for each of the selected advertisers, and the results of thesearch by each advertiser are then returned to the visitor. The returnedsearch results may be displayed on the same webpage or on a differentwebpage.

FIG. 9A illustrates an exemplary interface for a comparison shoppingwidget 910. A web page 912 includes the widget 910. Widget 910 may belocated within one window of the interface (e.g., a “primary” window),or within a separate window of the interface (e.g., a “pop-up” or“secondary” window). Widget 910 may have one or more advertiserselection controls such as check boxes 914 located proximate to anadvertiser name, and a search button or select button 916. It should beunderstood that selection controls are not limited to check-boxes, forexample, radio buttons or other similar controls may also be used.

In one embodiment, widget 910 includes a list of one or more advertisernames, and a corresponding check-box for each advertiser name. When thevisitor chooses to request a search using widget 910, the search will beperformed for or by each of the selected advertisers. In anotherembodiment, widget 910 may include additional information, includingspecific information related to information previously provided by theuser. For example, if a visitor has already begun to search for airlineflights from Tuscaloosa to Tahiti, widget 910 may include “Tahiti RoyalHotel, Stay 2 nights, Get 1 night free!” along with a correspondingcheck-box. A web address, phone number, or other advertising informationmay also be supplied.

According to one embodiment, when a visitor selects one or more of thecheck boxes 914 and clicks on the search button 916, a search isperformed by or for each of the selected advertisers. The searchincludes search terms that may be provided, for example, by the visitoron the web page 912. Search terms may also be dynamically generatedbased on other information received from the visitor, such as the user'sfrequent flier status, travel preferences, purchase history, or similarvisitor-specific information. The results of the search (for example, anad 920) may be provided within the web page 912 or in another, separateweb page (not shown) hosted by a publisher of the website or by anotherpublisher.

FIG. 9B illustrates an exemplary method of one implementation of aconsumer shopping widget. An exemplary process begins at block 950. Atblock 952, a search query is received. The search query may be generatedby a visitor interacting with an e-commerce website, such as a travelsearch website, and sent to a media platform, such as media platform 201shown in FIG. 2. For example, the visitor may request a search for hotelrooms in Times Square, New York City.

At block 954, a multi-click search interface is displayed to the user inan interface of, e.g., a client computer. The multi-click searchinterface may be generated by, for example, media platform 201 (as shownin FIG. 2), by a publisher of the e-commerce website, or by athird-party. The multi-click search interface may be similar to widget910 as described in FIG. 9A. For example, the multi-click interface maydisplay one or more advertisers of hotels in New York City, or morespecifically, in or near Times Square, along with a correspondingcheck-box for each advertiser. The multi-click interface may alsoinclude a search button (e.g., a button labeled “SEARCH”), or otheractivation control, to request search results from any of the selectedadvertisers. At block 956, a multi-click search request is received, forexample, by media platform 201. The request may be generated, forexample, by a visitor selecting one or more advertisers in a multi-clicksearch interface and also by selecting a search or execute button. Atblock 958, the search query received above at block 952 may be sent to,for example, each of the selected advertisers, or to another searchservice (e.g., a search service that performs a search on behalf of theadvertiser, which may be the same search service that provides contentfor the e-commerce website).

At block 960, results of the search query request may be received by oneor more of the selected advertisers and displayed to the visitor. Thesearch results may be displayed, for example, in a single window of aweb page, or in separate windows. At block 962, the process ends.

Exemplary Media Platform Components

FIG. 10 illustrates an exempary media platform 1000 comprising one ormore of the following components:

An intent taxonomy component 1002 allows for the creation and managementof a structured library of intent targets and intent stages (or processcontexts), which is referred to as an intent taxonomy. The intenttargets and/or intent stages may be categorized by a vertical market(e.g., travel, electronics). The intent taxonomy includes a data modelthat enables publishers, advertisers and others to interact with themedia platform. The library may be stored in a database.

A translation engine 1004 allows for the creation and management of amapping of diverse intent targets and/or intent stages into a normalizedintent taxonomy. For example, the intent targets and/or intent stagesmay be provided by the publisher in an ad tag, a cookie, and/or a HTTPheader.

A hurdle rate engine 1006 stores hurdle rate inputs such as expectedconversion/contribution assumptions for a specific intent, plusadjustment assumptions for variables such as user type, traffic source,intent stage and lifetime value. Hurdle rate inputs can be inputmanually (i.e. via a file upload and/or UI) or be dynamically learnedand/or stored through cookies served by ads or pixels. This componentalso includes the real-time calculation of hurdle rates (based on thehurdle rate inputs) upon receipt of a publisher ad request.

A user account component 1008 allows for the creation and management ofprofiles for the various entities participating in the marketplace,including advertisers, publishers, and others. Specific roles,permissions, and other information (e.g., names, contact info, etc.) canbe created and managed.

A publisher site inventory component 1010 allows publishers to createand manage ad slots, along with rules and information associated withthose ad slots (e.g. size, targeting rules, hurdle rate options,allowable media types/use cases, and style sheets).

An ad campaign component 1012 allows advertisers to create and managecampaigns and bid groups including the creation and management ofbudgets, bids, and intent targeting rules. The ad campaign componentincludes a file upload feature that enables a user to upload apre-formatted file (i.e. Excel or .csv) into the campaign database.

An ad creatives component 1014 allows for the uploading and managementof ad creatives and the association of those creatives to campaigns andbid groups. The ad creatives component also includes a service fordynamically generating highly relevant landing page URLs based onadvertiser specifications and/or a dynamic determination of visitorintent.

A campaign mapping component 1016 allows for the efficient translationof an SEM campaign (e.g. for AdWords) or a comparison shopping engine(CSE) campaign e.g. for Shopping.com) into the media platform by mappingad groups, keywords, creatives, product SKU feeds, and other informationinto a campaign structure and taxonomy of the media platform.

A reporting and analytics component 1018 provides detailed data andreports to all entities utilizing the media platform, including reportson A/B testing, campaign performance, page performance, availablecampaigns and creatives, and other information.

A matching decision engine 1020 creates a “candidate list” of eligibleadvertisements for a given publisher ad request based on targeting rulesand a hurdle rate (set by the hurdle rate engine).

An optimization decision engine 1022 selects and ranks specific ads fromthe candidate list in order to optimize business results. Theoptimization decision engine allows users of the media platform tocreate and manage rules to influence optimization decisions.

A serving and logging component 1024 receives requests from publishers(including data extracted from some combination of ad tag, cookie andHTTP header info), serves ads, updates cookie information and logsoutcomes such as click-through rate and return rate.

A billing component 1026 enables billing and processing of payments fromadvertisers to publishers through a third party. The third party maymodify the payments based on commissions and other adjustments.

A user interface component 1028 allows users to access and edit data andrules through user interfaces and across multiple components of themedia system.

An application programming interface 1030 (API) enables support forfunctionality of the components of the media system.

A relevance type mapping component 1032 streamlines the process ofdesignating a relevance type for an ad targeting a specific intent.

Exemplary General Purpose Computer System

Various embodiments according to the present invention may beimplemented on one or more computer systems. These computer systems maybe, for example, general-purpose computers such as those based on IntelPENTIUM-type processor, Motorola PowerPC, AMD Athlon or Turion, SunUltraSPARC, Hewlett-Packard PA-RISe processors, or any other type ofprocessor. It should be appreciated that one or more of any typecomputer system may be used to determine ad placement according tovarious embodiments of the invention. Further, the system may be locatedon a single computer or may be distributed among a plurality ofcomputers attached by a communications network.

A general-purpose computer system according to one embodiment of theinvention is configured to perform any of the described functions,including but not limited to, determining user intent, intent stage orcontext, process context, hurdle rate, and obtaining and displayingadvertisements based at least on the intent and hurdle rate. It shouldbe appreciated that the system may perform other functions, including,but not limited to, storing and/or managing the historical behavior ofusers, monitoring the conversion of return users, maintaining a databaseof advertising campaigns, maintaining a database of translation maps,determining hurdle rates in real-time responsive to conversions, etc.,and it should also be appreciated that the invention is not limited tohaving any particular function or set of functions.

FIG. 11 shows a block diagram of a general purpose computer and networksystem 1100 in which various aspects of the present invention may bepracticed. For example, various aspects of the invention may beimplemented as specialized software executing in one or more computersystems including general-purpose computer system 1101 shown in FIG. 11.Computer system 1101 may include a processor 1104 connected to one ormore memory devices 1105, such as a disk drive, memory, or other devicefor storing data. Memory 1105 is typically used for storing programs anddata during operation of the computer system 1101. Components ofcomputer system 1101 may be coupled by an interconnection mechanism suchas network 1110, which may include one or more busses (e.g., betweencomponents that are integrated within a same machine) and/or a network(e.g., between components that reside on separate discrete machines).The interconnection mechanism enables communications (e.g., data,instructions) to be exchanged between system components of system 1101.

Computer system 1101 also includes one or more input/output (I/O)devices 1106, for example, a keyboard, mouse, trackball, microphone,touch screen, a printing device, display screen, speaker, etc. Inaddition, computer system 1101 may contain one or more interfaces (e.g.,network communication device 1108) that connect computer system 1101 toa communication network (in addition or as an alternative to the network1110).

Storage system 1109 typically includes a computer readable and writeablenonvolatile recording medium in which signals are stored that define aprogram to be executed by the processor or information stored on or inthe medium to be processed by the program. The medium may, for example,be a disk or flash memory. Typically, in operation, the processor causesdata to be read from the nonvolatile recording medium into anothermemory that allows for faster access to the information by the processorthan does the medium. This memory is typically a volatile, random accessmemory such as a dynamic random access memory (DRAM) or static memory(SRAM). The memory may be located in storage system 1109, as shown, orin memory system 1105. The processor 1104 generally manipulates the datawithin the integrated circuit memory 1104, and then copies the data tothe medium associated with storage 1109 after processing is completed. Avariety of mechanisms are known for managing data movement between themedium and integrated circuit memory element and the invention is notlimited thereto. The invention is not limited to a particular memorysystem or storage system.

The computer system may include specially-programmed, special-purposehardware, for example, an application-specific integrated circuit(ASIC). Aspects of the invention may be implemented in software,hardware or firmware, or any combination thereof. Further, such methods,acts, systems, system elements and components thereof may be implementedas part of the computer system described above or as an independentcomponent.

Although computer system 1101 is shown by way of example as one type ofcomputer system upon which various aspects of the invention may bepracticed, it should be appreciated that aspects of the invention arenot limited to being implemented on the computer system as shown in FIG.11. Various aspects of the invention may be practiced on one or morecomputers having a different architectures or components than that shownin FIG. 11.

Computer system 1101 may be a general-purpose computer system that isprogrammable using a high-level computer programming language. Computersystem 1101 may be also implemented using specially programmed, specialpurpose hardware. In computer system 1101, processor 1104 is typically acommercially-available processor such as the well-known Pentium classprocessor available from the Intel Corporation, although many otherprocessors are available. Such a processor usually executes an operatingsystem which may be, for example, the Windows-based operating systemsavailable from the Microsoft Corporation, the MAC OS operating systemavailable from Apple Computer, one or more of the Linux-based operatingsystem distributions (e.g., the Enterprise Linux operating systemavailable from Red Hat Inc.), the Solaris operating system availablefrom Sun Microsystems, or UNIX operating systems available from varioussources. It should be understood that the invention is not limited toany particular operating system.

The processor and operating system together define a computer platformfor which application programs in high-level programming languages arewritten. It should be understood that the invention is not limited to aparticular computer system platform, processor, operating system, ornetwork. Also, it should be apparent to those skilled in the art thatthe present invention is not limited to a specific programming languageor computer system. Further, it should be appreciated that otherappropriate programming languages and other appropriate computer systemscould also be used.

One or more portions of the computer system may be distributed acrossone or more computer systems coupled to a communications network. Thesecomputer systems also may be general-purpose computer systems. Forexample, various aspects of the invention may be distributed among oneor more computer systems (e.g., servers) configured to provide a serviceto one or more client computers, or to perform an overall task as partof a distributed system. By way of further example, various aspects ofthe invention may be performed on a client-server or multi-tier systemthat includes components distributed among one or more server systemsthat perform various functions according to various embodiments of theinvention. These components may be executable, intermediate (e.g., IL)or interpreted (e.g., Java) code which communicate over a communicationnetwork (e.g., the Internet) using a communication protocol (e.g.,TCP/IP).

It should be appreciated that the invention is not limited to executingon any particular system or group of systems. Also, it should beappreciated that the invention is not limited to any particulardistributed architecture, network, or communication protocol.

Various embodiments of the present invention may be programmed using anobject-oriented programming language, such as SmallTalk, Java, C++, Ada,or C# (C-Sharp). Other object-oriented programming languages may also beused. Alternatively, functional, scripting, and/or logical programminglanguages may be used. Various aspects of the invention may beimplemented in a non-programmed environment (e.g., documents created inHTML, XML or other format that, when viewed in a window of a browserprogram, render aspects of a graphical-user interface (GUI) or performother functions). Various aspects of the invention may be implemented asprogrammed or non-programmed elements, or any combination thereof.

Various aspects of this system can be implemented by one or more systemswithin system 1100. For instance, the system may be a distributed system(e.g., client server, multi-tier system). In one example, the systemincludes software processes executing on a system associated with a user(e.g., a client system). These systems may permit the user to determinea user's context and/or intent as expressed within an ecommerce site,and to provide advertisements from other ecommerce sites, and to displaythem to the user.

Having thus described several aspects of at least one embodiment of thisinvention, it is to be appreciated various alterations, modifications,and improvements will readily occur to those skilled in the art. Suchalterations, modifications, and improvements are intended to be part ofthis disclosure, and are intended to be within the spirit and scope ofthe invention. Accordingly, the foregoing description and drawings areby way of example only.

What is claimed is:
 1. A distributed computer system comprising: ane-commerce component adapted to determine a context of a user operatinga client computer to interact with an e-commerce website; a translationengine operable to translate the context into one or more contexttargets; a hurdle rate engine operable to determine, based on the one ormore context targets, a hurdle rate that identifies a threshold amountto be bid by an advertiser in order to display an advertisement to theuser; a decision engine operable to select, from a plurality ofadvertisements each having a respective bid, an optimal advertisement tobe displayed to the user, the optimal advertisement having a respectivebid that exceeds the hurdle rate; and a delivery component adapted todisplay the optimal advertisement to the user.
 2. The system accordingto claim 1, further comprising a candidate advertisement engine operableto generate a list of candidate advertisements based on the context ofthe user.
 3. The system according to claim 1, further comprising anoptimization engine operable to determine a contribution per visitoroutcome for each of one or more advertisements of the plurality ofadvertisements.
 4. The system according to claim 3, wherein thecontribution per visitor outcome is based on the hurdle rate.
 5. Thesystem according to claim 3, wherein the contribution per visitoroutcome is based on an expected return to purchase value.
 6. The systemaccording to claim 3, further comprising a segmentation engine operableto identify a relationship between the user and a publisher.
 7. Thesystem according to claim 6, wherein the contribution per visitoroutcome is based on the relationship between the user and the publisher.8. The system according to claim 3, wherein the contribution per visitoroutcome is a positive contribution per visitor outcome, and wherein theoptimal advertisement further has a positive contribution per visitoroutcome.
 9. The system according to claim 1, further comprising anoutcome engine operable to analyze an outcome of displaying the optimaladvertisement to the user.
 10. The system according to claim 1, furthercomprising a translation database coupled to the translation engine. 11.The system according to claim 1, further comprising a hurdle ratedatabase coupled to the hurdle rate engine.
 12. The system according toclaim 2, further comprising an advertising campaign database coupled tothe candidate advertisement engine.
 13. The system according to claim 3,further comprising an optimization database coupled to the optimizationengine.
 14. The system according to claim 1, wherein the deliverycomponent includes an advertisement interface of the client computercoupled to the decision engine.
 15. The system according to claim 1,further comprising a bid component operable to receive, from anadvertiser, at least one bid for one or more of the plurality ofadvertisements.
 16. A method of delivering advertising in an onlineenvironment comprising acts of: determining an intent of a userinteracting with an e-commerce website; determining a hurdle rate, basedat least on the intent of the user, that identifies a threshold amountto be bid by an advertiser in order to display an advertisement to theuser interacting with the e-commerce website; selecting, from aplurality of advertisements, an optimal advertisement having anadvertiser bid that exceeds the determined hurdle rate; and displayingthe optimal advertisement to the user in an interface of a clientcomputer system.
 17. The method according to claim 16, furthercomprising receiving, from a publisher of the e-commerce website, anadvertisement request.
 18. The method according to claim 17, wherein theadvertisement request includes one or more keywords, and wherein theintent of the user is based at least in part on the one or morekeywords.
 19. The method according to claim 17, further comprisingtranslating the advertisement request into one or more intent targets.20. The method according to claim 19, wherein translating theadvertisement request includes selecting each of the one or more intenttargets from a plurality of normalized intent targets based oninformation included in the advertisement request, and wherein theplurality of normalized intent targets is stored in an intent targettaxonomy database.
 21. The method according to claim 19, whereindetermining the hurdle rate includes adjusting the hurdle rate inrelation to the one or more intent targets.
 22. The method according toclaim 19, wherein determining the hurdle rate includes adjusting thehurdle rate based on a historical average conversion rate of each of theone or more intent targets.
 23. The method according to claim 19,wherein determining the hurdle rate includes adjusting the hurdle ratebased on an average contribution margin of a completed transaction forthe one or more intent targets.
 24. The method according to claim 16,wherein determining the intent of the user further includes translatingthe advertisement request into one or more process contexts.
 25. Themethod according to claim 24, wherein translating the advertisementrequest includes selecting each of the one or more process contexts froma plurality of normalized process contexts based on information includedin the advertisement request, and wherein the plurality of normalizedprocess contexts is stored in a process context taxonomy database. 26.The method according to claim 24, wherein determining the hurdle rateincludes adjusting the hurdle rate based on the one or more processcontexts.
 27. The method according to claim 16, further comprisingselecting, from the plurality of advertisements, one or more candidateadvertisements, and wherein the optimal advertisement is selected fromthe one or more candidate advertisements.
 28. The method according toclaim 27, wherein each of the one or more candidate advertisements isselected based on the hurdle rate.
 29. The method according to claim 27,wherein each of the one or more candidate advertisements is selectedbased on a relationship between the user and the publisher.
 30. Themethod according to claim 27, further comprising determining, for eachof the one or more candidate advertisements, an advertisement revenuepotential, and wherein the selected optimal advertisement has anadvertisement revenue potential exceeding the determined advertisementrevenue potential of each of the others of the one or more candidateadvertisements.
 31. The method according to claim 30, wherein theadvertisement revenue potential is based on a return to visit rate. 32.The method according to claim 30, wherein the advertisement revenuepotential is based on an expected return to purchase value.
 33. Themethod according to claim 30, wherein the advertisement revenuepotential is based on a fully loaded expected transaction value.
 34. Themethod according to claim 16, wherein the optimal advertisement isassociated with a relevance type selected by the publisher.
 35. Themethod according to claim 34, wherein the relevance type is one ofretailer discovery, substitute discovery, and complement discovery. 36.The method according to claim 16, further comprising generating adynamic uniform resource locator based on the intent of the user, andincluding the dynamic uniform resource locator within the optimaladvertisement.
 37. The method according to claim 16, further comprisingconfiguring a creative content of the optimal advertisement such thatthe creative content targets the intent of the user.
 38. The methodaccording to claim 16, wherein the hurdle rate is based on one or moreoutcomes related to displaying the optimal advertisement to the user.39. A method of delivering advertising in an online environmentcomprising acts of: identifying a characteristic of a user interactingwith an e-commerce website; determining a hurdle rate for displaying anadvertisement to the user at the e-commerce website based at least onthe determined characteristic of the user; determining whether todisplay an advertisement to the user based on the characteristic of theuser, and, if so, selecting an advertisement from a plurality ofadvertisements based on an intent of the user, wherein the selectedadvertisement is offered by an advertiser for at least the hurdle rate;and delivering the selected advertisement to the user in an interface ofa client computer system.
 40. The method according to claim 39, furthercomprising receiving an advertisement request from a publisher.
 41. Themethod according to claim 40, wherein the advertisement request includesthe characteristic of the user.
 42. The method according to claim 39,wherein the characteristic of the user is one of past purchaser andnon-past purchaser.
 43. The method according to claim 39, wherein thecharacteristic of the user is loyalty program member.
 44. The methodaccording to claim 39, wherein the characteristic of the user is basedon historical data provided by the publisher.
 45. The method accordingto claim 39, wherein the characteristic of the user is based on theintent of the user.
 46. The method according to claim 39, wherein thecharacteristic of the user is based on at least one visitor acquisitionmechanism.
 47. The method according to claim 46, wherein the visitoracquisition mechanism is at least one of a paid search, a naturalsearch, and an e-mail.
 48. The method according to claim 39, wherein thecharacteristic of the user is based on an inter-session behavior of theuser.
 49. The method according to claim 39, wherein the characteristicof the user is based on an intra-session behavior of the user.
 50. Themethod according to claim 39, wherein the characteristic of the user iscollected from one of the e-commerce website and the client computersystem.
 51. The method according to claim 39, wherein determining thehurdle rate includes adjusting the hurdle rate based on thecharacteristic of the user.
 52. The method according to claim 39,wherein the characteristic is one of a high value visitor and a lowvalue visitor.
 53. A computer readable medium having stored thereonsequences of instructions including instructions that will cause aprocessor to perform a method of delivering advertising comprising actsof: determining an intent of a user interacting with an e-commercewebsite; determining a hurdle rate, based at least on the intent of theuser, that identifies a threshold amount to be bid by an advertiser inorder to display an advertisement to the user interacting with thee-commerce website; selecting, from a plurality of advertisements, anoptimal advertisement having an advertiser bid that exceeds thedetermined hurdle rate; and displaying the optimal advertisement to theuser in an interface of a client computer system.
 54. A computerreadable medium having stored thereon sequences of instructionsincluding instructions that will cause a processor to perform a methodof delivering advertising comprising acts of: identifying acharacteristic of a user interacting with an e-commerce website;determining a hurdle rate for displaying an advertisement to the user atthe e-commerce website based at least on the determined characteristicof the user; determining whether to display an advertisement to the userbased on the characteristic of the user, and, if so, selecting anadvertisement from a plurality of advertisements based on an intent ofthe user, wherein the selected advertisement is offered by an advertiserfor at least the hurdle rate; and delivering the selected advertisementto the user in an interface of a client computer system.